i)
applying a tailored inexact sequential quadratic programming (SQP) algorithm
 [1]}, [2]}
to solve the GP-MPC optimal control problems, returning suboptimal, yet feasible solutions at convergence;
ii)
speeding up GP computations by efficient inference and automatic differentiation (AD) [3]}, [4]}, as well as parallelization on a graphical processing unit (GPU);
iii)
showing that the resulting algorithm maintains favorable local convergence properties if the GP posterior covariance and process noise covariance at the solution are sufficiently small.

